4.5 Article

Finite Element Analysis of Tricuspid Valve Deformation from Multi-slice Computed Tomography Images

Journal

ANNALS OF BIOMEDICAL ENGINEERING
Volume 46, Issue 8, Pages 1112-1127

Publisher

SPRINGER
DOI: 10.1007/s10439-018-2024-8

Keywords

Multi-slice computed tomography; Tricuspid valve; Finite element analysis; Patient-specific geometries; Biomechanics

Funding

  1. NIH [HL104080, HL127570]

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Despite the growing clinical interest in the tricuspid valve (TV), there is an incomplete understanding of TV biomechanics which is important in normal TV function and successful TV repair techniques. Computational models with patient-specific human TV geometries can provide a quantitative understanding of TV biomechanic. Therefore, this study aimed to develop finite element (FE) models of human TVs from multi-slice computed tomography (MSCT) images to investigate chordal forces and leaflet stresses and strains. Three FE models were constructed for human subjects with healthy TVs from MSCT images and incorporated detailed leaflet geometries, realistic nonlinear anisotropic hyperelastic material properties of human TV, and physiological boundary conditions tracked from MSCT images. TV closure from diastole to systole was simulated. Chordal lengths were iteratively adjusted until the simulated TV geometries were in good agreement with the true geometries reconstructed from MSCT images at systole. Larger chordal forces were found on the strut (or basal) chords than on the rough zone chords and the total forces applied on the anterior papillary muscles by the strut chords were higher than those on the posterior or septal papillary muscles. At peak systolic pressure, the average maximum stress on the middle sections of the leaflets ranged from 30 to 90 kPa, while the average maximum principal strain values ranged from 0.16 to 0.30. The results from healthy TVs can serve as baseline biomechanical metrics of TV mechanics and may be used to inform TV repair device design. The computational approach developed could be one step towards developing computational models that may support pre-operative planning in complex TV repair procedures in the future.

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